podcast

VoxFlow Podcast Skill

Generate multi-speaker AI podcasts entirely from the command line. Sister skills:

• Simple TTS / narration / voice search → voxflow (hub)
• Short videos / AI clips / knowledge cards → voxflow:video
• Transcribe / translate subtitles / dub → voxflow:transcribe

Prerequisites

• Node.js ^20.19.0 || >=22.12.0
• npm install -g voxflow then voxflow login
• VoxFlow account (free tier: 10K quota/month)

No API keys needed — all auth goes through voxflow login.

Quick Start

# 1. Login (one-time, opens browser)
voxflow login

# 2. Generate a podcast
voxflow podcast --topic "AI 时代的程序员出路"

# 3. Output: podcast-2026-03-20T12-00-00.wav + .txt

Full Workflow

Step 1: Generate Script Only

voxflow podcast \
  --topic "量子计算入门" \
  --template tutorial \
  --colloquial medium \
  --speakers 2 \
  --language zh-CN \
  --format json \
  --no-tts

Outputs: podcast-<ts>.txt + podcast-<ts>.podcast.json

Step 2: Review & Edit

Open .podcast.json — it contains structured dialogue, speaker info, quality scores, and voice mappings. Edit as needed.

Step 3: Synthesize from File

voxflow podcast --input podcast-2026-03-20.podcast.json --output final.wav

One-Shot (generate + synthesize)

voxflow podcast \
  --topic "Web3 的未来" \
  --engine ai-sdk \
  --colloquial high \
  --speakers 3 \
  --output web3-podcast.wav

Parameters

Flag	Values	Default	Description
--topic	text	tech trends	Podcast topic or prompt
--engine	auto, legacy, ai-sdk	auto (→ ai-sdk)	Generation engine
--template	interview, discussion, news, story, tutorial	interview	Podcast template
--colloquial	low, medium, high	medium	Conversational tone level
--speakers	1, 2, 3	2	Number of speakers
--language	zh-CN, en, ja	zh-CN	Output language
--length	short, medium, long	medium	Script length
--format	json	—	Also output .podcast.json
--input	file path	—	Load .podcast.json for synthesis
--no-tts	flag	false	Script only, skip TTS
--speed	0.5-2.0	1.0	TTS playback speed
--silence	0-5.0	0.5	Gap between segments (sec)
--output	file path	auto	Output file path

Engine Comparison

Feature	legacy	ai-sdk
Structured output	No	Yes (JSON)
Quality scoring	No	Yes (1-10)
Colloquial control	No	3 levels
Intent tagging	No	Yes
Speaker metadata	Partial	Full
Multi-language	Chinese only	zh/en/ja

Templates

• interview — Host + Guest deep conversation
• discussion — Roundtable multi-person discussion
• news — Professional news briefing
• story — Multi-character story narration
• tutorial — Teacher + Student educational dialogue

Quota Cost

Operation	Cost
Script generation (medium, ~16 turns)	2,000
TTS per turn (native pause voice)	50
TTS per chunk (splice fallback voice)	50

Per-turn TTS call count depends on voice: voices flagged nativePauseSupported: true (most podcast voices) take 1 TTS call per turn — TRTC honors <|break|> / <|s_break|> markers natively (~250-430ms inserted). Voices that haven't been verified (e.g. 旁白 narration voices) fall back to client-side splice = N calls per turn.

Typical medium podcast (16 turns, all native voices) ≈ 16 × 50 + 2,000 = 2,800 quota — Free tier (10K/month) covers ~3 medium podcasts. Tip: if you already have a script, pass --script my.json to skip the 2,000 LLM step entirely. Mixed-voice podcasts cost slightly more if they include non-native voices.

Examples

# English tech podcast
voxflow podcast --topic "AI ethics debate" --language en --template discussion

# Quick news briefing (short)
voxflow podcast --topic "本周科技新闻" --template news --length short

# Casual chat with high colloquial level
voxflow podcast --topic "程序员加班那些事" --colloquial high

# JSON export for editing
voxflow podcast --topic "创业故事" --format json --no-tts

# Synthesize edited script
voxflow podcast --input edited-podcast.podcast.json --speed 1.1

Rules

1. Check quota first — medium podcast ≈ 5K. Run voxflow status before generation.
2. Iterate on the script — use --no-tts --format json to inspect dialogue before paying for TTS.
3. Voice mapping — for ai-sdk engine, the .podcast.json includes per-speaker voice IDs. Edit them before re-running with --input.
4. Auto-play when done: open podcast-*.wav.